An introduction of the data and a description of the trends/books/items you are choosing to analyze (and why!)
Write a summary paragraph of findings that includes the 5 values calculated from your summary information R script
These will likely be calculated using your DPLYR skills, answering questions such as:
Feel free to calculate and report values that you find relevant.
This data was collected and published by the Seattle Public Library.
The data collected include the format, year, month, and number of checkouts per book. It also includes the title, the author(s), publishers, genre, and publication year of the book.
Through
Federal mandate to publicise data
length of checkout
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Include a chart. Make sure to describe why you included the chart, and what patterns emerged
The first chart that you will create and include will show the trend over time of your variable/topic/interest. Think carefully about what you want to communicate to your user (you may have to find relevant trends in the dataset first!). Here are some requirements to help guide your design:
When we say “clear” or “human readable” titles and labels, that means that you should not just display the variable name.
Here’s an example of how to run an R script inside an RMarkdown file:
## `summarise()` has grouped output by 'Title'. You can override using the
## `.groups` argument.
Include a chart. Make sure to describe why you included the chart, and what patterns emerged
The second chart that you will create and include will show another trend over time of your variable/topic/interest. Think carefully about what you want to communicate to your user (you may have to find relevant trends in the dataset first!). Here are some requirements to help guide your design:
When we say “clear” or “human readable” titles and labels, that means that you should not just display the variable name.
Here’s an example of how to run an R script inside an RMarkdown file:
## `summarise()` has grouped output by 'Title'. You can override using the
## `.groups` argument.
The last chart is up to you. It could be a line plot, scatter plot, histogram, bar plot, stacked bar plot, and more. Here are some requirements to help guide your design:
Here’s an example of how to run an R script inside an RMarkdown file:
## `summarise()` has grouped output by 'date'. You can override using the
## `.groups` argument.